The NNSYSID Toolbox - A MATLAB Toolbox for System Identification with Neural Networks

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

1990 Downloads (Pure)

Abstract

To assist the identification of nonlinear dynamic systems, a set of tools has been developed for the MATLAB(R) environment. The tools include a number of different model structures, highly effective training algorithms, functions for validating trained networks, and pruning algorithms for determination of optimal network architectures. The toolbox should be regarded as a nonlinear extension to the system identification toolbox provided by The MathWorks, Inc. This paper gives a brief overview of the entire collection of toolbox functions
Original languageEnglish
Title of host publicationProceedings of the 1996 IEEE Symposium on Computer-Aided Control System Design
Place of PublicationDearborn, Michigan, USA
PublisherIEEE
Publication date1996
Pages374-379
ISBN (Print)0-7803-3032-3
DOIs
Publication statusPublished - 1996
Event1996 IEEE Symposium on Computer-Aided Control System Design - Dearborn, Michigan, USA
Duration: 1 Jan 1996 → …

Conference

Conference1996 IEEE Symposium on Computer-Aided Control System Design
CityDearborn, Michigan, USA
Period01/01/1996 → …

Bibliographical note

Copyright: 1996 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

Fingerprint

Dive into the research topics of 'The NNSYSID Toolbox - A MATLAB Toolbox for System Identification with Neural Networks'. Together they form a unique fingerprint.

Cite this